A good data model is the difference between a report that works and one you keep fighting with. Yet modelling is often skipped or treated as an afterthought. In this workshop we lay the foundation: what's a fact table, what's a dimension, how do you set up relationships, and why does that make everything you build on top of it better?
What you'll learn
We go back to the core of data modelling. Not as a theoretical lecture, but as a practical skill you can apply right away in Power BI, Fabric or any other tool.
- The difference between facts and dimensions (and why it matters)
- Setting up star schemas that are correct and scalable
- Understanding relationships: cardinality, filter direction, active vs. inactive
- Recognising and preventing common mistakes
Who is this for?
- BI professionals who notice their DAX is getting complicated because of a messy model
- Analysts who want to understand why their report is slow or gives odd numbers
- Teams that want to agree on a shared modelling approach
Some experience with Power BI or similar tooling is helpful. Want the full Power BI picture? Have a look at the PL-300 training.
How I approach this
We work on your own data where possible, so it's immediately recognisable. The structure is the same as all my training formats: understanding over completeness, and always focused on what you can do with it yourself. More about that on the way of working page.
Sounds good?
Leave your name and email and tell me a bit about your situation. We'll find a moment to talk it through.
Or explore: all training formats · way of working · contact page